Modeling and convergence analysis of a continuous multi-objective differential evolution algorithm

Abstract

This paper reports a mathematical modeling and convergence analysis of a continuous multi-objective differential evolution (C-MODE) algorithm that is proposed very recently. This C-MODE is studied in the context of global random search. The convergence of the population to the Pareto optimal solutions with probability one is developed. In order to facilitate the understanding of the C-MODE operators in a continuous space, a mathematical analysis of the operators is conducted based upon a Gaussian distributed initial population. A set of guidelines is derived for the parameter setting of the C-MODE based on the theoretical results from the mathematical analysis. A simulation analysis on a specific numerical example is conducted to validate the mathematical analytical results and parameter-setting guidelines. The performance comparison based on a suite of complex benchmark functions also demonstrates the merits of such parameter-setting guidelines